Upload app.py

app.py

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+import gradio as gr
+import requests
+import base64
+from PIL import Image
+import io
+import os
+
+API_KEY = os.environ.get("API_KEY")
+API_URL = "https://api.4llm.com/v1/images/generations"
+
+def generate_image(prompt, size="1024x1024"):
+    headers = {
+        "Authorization": f"Bearer {API_KEY}",
+        "Content-Type": "application/json"
+    }
+    
+    data = {
+        "model": "4llm-image",
+        "prompt": prompt,
+        "n": 1,
+        "size": size
+    }
+    
+    try:
+        response = requests.post(API_URL, headers=headers, json=data)
+        response.raise_for_status()
+        result = response.json()
+        
+        # Get the base64 image data
+        image_data = result["data"][0]["url"].split(",")[1]
+        image_bytes = base64.b64decode(image_data)
+        
+        # Convert to PIL Image
+        image = Image.open(io.BytesIO(image_bytes))
+        return image, result["data"][0]["revised_prompt"]
+    except Exception as e:
+        return None, f"Error: {str(e)}"
+
+# Create the Gradio interface
+with gr.Blocks(title="4LLM Image Generation") as demo:
+    gr.Markdown("# 4LLM Image Generation Demo")
+    gr.Markdown("Generate images using the 4LLM API with no rate limits!")
+    
+    with gr.Row():
+        with gr.Column():
+            prompt = gr.Textbox(
+                label="Prompt",
+                placeholder="Describe the image you want to generate...",
+                lines=3
+            )
+            size = gr.Dropdown(
+                choices=["1024x1024", "512x512", "768x768"],
+                value="1024x1024",
+                label="Image Size"
+            )
+            generate_btn = gr.Button("Generate Image")
+        
+        with gr.Column():
+            output_image = gr.Image(label="Generated Image")
+            revised_prompt = gr.Textbox(
+                label="Revised Prompt",
+                lines=3,
+                interactive=False
+            )
+    
+    generate_btn.click(
+        fn=generate_image,
+        inputs=[prompt, size],
+        outputs=[output_image, revised_prompt]
+    )
+
+if __name__ == "__main__":
+    demo.launch(share=False)